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01_​Sentiment_​Analysis_​ML_​Approach

01_Machine Learning Approach for Sentiment Analysis

This is an example of sentiment analysis using machine learning. The IMDB data set contains movie reviews labelled by sentiment. A Machine Learning algorithm is then trained to predict the sentiment of such reviews in the training set and applied to the reviews in the test set to evaluate its generalization performance.

Machine Learning Approach for Sentiment Analysis This is an example of sentiment analysis using machine learning. The IMDB data set contains movie reviews labelled by sentiment. A Machine Learning algorithm is then trained to predict thesentiment of such reviews in the training set and applied to the reviews in the test set to evaluate its generalization performance. Dataset ReferenceAndrew L. Maas, Raymond E. Daly, Peter T. Pham, Dan Huang, Andrew Y. Ng, and Christopher Potts. (2011). Learning Word Vectors for Sentiment Analysis. The 49th Annual Meeting of the Associationfor Computational Linguistics (ACL 2011). Read articles from IMDB datasetColor by sentimentlabelto word vectorApply decisiontree modelExtract labelVisualize wronglyclassified documentscleaningstemmingtag filteringto wordvector30 keywords30 keywordskeep keywordsin > 5 DocumentsExtract labelScore decisiontree model Reading Data Color Manager Document Vector Decision TreePredictor Category To Class DecisionTree Learner Document Viewer Pre-processing DocumentVector Applier Keygraph KeywordExtractor Keygraph KeywordExtractor Limit # keywords Category To Class Partitioning Prepare Output Model Writer Scorer Machine Learning Approach for Sentiment Analysis This is an example of sentiment analysis using machine learning. The IMDB data set contains movie reviews labelled by sentiment. A Machine Learning algorithm is then trained to predict thesentiment of such reviews in the training set and applied to the reviews in the test set to evaluate its generalization performance. Dataset ReferenceAndrew L. Maas, Raymond E. Daly, Peter T. Pham, Dan Huang, Andrew Y. Ng, and Christopher Potts. (2011). Learning Word Vectors for Sentiment Analysis. The 49th Annual Meeting of the Associationfor Computational Linguistics (ACL 2011). Read articles from IMDB datasetColor by sentimentlabelto word vectorApply decisiontree modelExtract labelVisualize wronglyclassified documentscleaningstemmingtag filteringto wordvector30 keywords30 keywordskeep keywordsin > 5 DocumentsExtract labelScore decisiontree modelReading Data Color Manager Document Vector Decision TreePredictor Category To Class DecisionTree Learner Document Viewer Pre-processing DocumentVector Applier Keygraph KeywordExtractor Keygraph KeywordExtractor Limit # keywords Category To Class Partitioning Prepare Output Model Writer Scorer

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Created by: Kilian
Created at: 2014-10-20
On NodePit since: 2024-06-28
Last update: 2025-10-13
Created with KNIME version: v4.5.0
Tags: BooksFrom Words To WisdomText Mining

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